(1)Models of the neuromuscular and the skeletal systems were developed based on results of analyzing responses of the neuromuscular system during electrical stimulation. Then, a basic simulation system of FES-induced motions for the paraplegics was developed. A stimulation pattern for standing up was made up automatically on the simulation system using the dynamic optimization.(2)It was verified that linear interpolation of EMG patterns and artificial neural network could be used for stimulation pattern generation. In addition, a system that patients could modify stimulation patterns without medical knowledge was developed and its capabilities were verified in experiments of controlling normal subjects' wrist angles.(3)The error detecting and correcting circuit (ECC) based on the Hamming coding was applied to an experimental implantable FES system for rejecting influence of external electromagnetic noise. Improvement of the reliability of transmitted stimulation data by using the ECC was verified on the preliminary implantable FES system.(4)It was suggested that the following two methods were useful in FES control for preventing the incontinence : 1) 180 degrees shift of the phase between stimulus pulses applying to the left and right pudendal nerves for high urethral closing force in short time. 2) stimulation to one of the pudendal nerves alternately for long time low closing force of the urethra.(5)Waveforms of nerve action potentials elicited by external mechanical stimulation were analyzed for extracting information for feed back control in FES application. Cluster analysis was found to be useful for estimating the stimulation that elicited the nerve signals.(6)Methods of getting control commands for FES system, which were based on the posterior auricular muscle, the tongue movement, and head movement identification by artificial neural network e.g. nodding, were confirmed to have fundamental feasibility of using in clinical application.